GOALI/CPS:Medium:A Framework for Enabling Energy-Aware Smart Facilities

拟议研究的目标是确定以低成本提供有关建筑物能源消耗的具体信息并促进保护的方法。将开发信号处理、机器学习和数据融合技术，从整个建筑的电能表和其他可用的传感器中提取可操作的信息。主要目标是：(a)通过从低成本的数据来源提取高价值的信息，建立一个框架，以获得有关建筑物用电量的分类、特定电器的反馈；(b)研究和开发数据挖掘和机器学习算法，以利用特定电器的电力数据，为用户提供如何优化其能源消耗的建议，并了解其能源相关决策的影响。宾夕法尼亚州匹兹堡的一系列住宅建筑将作为评估和验证我们提出的方法的试验台。Blueroof Technologies是一家位于宾夕法尼亚州McKeesport的非营利性公司，该公司研究、开发并提供具有集成传感器网络和建筑自动化系统的经济适用的老年人住房，该公司将为该项目提供他们的研究小屋。同样，全球领先的消费品和建筑技术供应商罗伯特博世有限责任公司将提供额外的技术研究援助和专业知识。该项目的主要科学价值在于制订了一个框架，根据能源使用分类方法促进节约能源的价值来评价它们。由此产生的数据集将足够大，足以得出有关该技术的可行性和有效性的重要结论，并允许开发有关建筑物中电器使用趋势和模式的新模型。这项研究的广泛影响包括通过低成本获取实时设备级数据，为未来的网络物理系统提供基础。这些数据可以通过揭示用户行为与建筑物用电量之间的关系来帮助降低建筑物的能耗。与博世的产学研合作将确保将技术和科学贡献导向创新解决方案，并在市场上得到实际应用。此外，该项目将通过与马里兰大学东岸分校（University of Maryland Eastern Shore）合作，吸引少数族裔学生，从而对多样性做出重大贡献。马里兰大学东岸分校是一所赠地的黑人大学，学生群体多样化。最后，一系列计划的工业研讨会、讲习班和期刊文章的出版将使这项工作得到进一步传播。

The goal of the proposed research is to identify ways to inexpensively provide specific information about energy consumption in buildings and facilitate conservation. Signal processing, machine learning, and data fusion techniques will be developed to extract actionable information from whole-building power meters and other available sensors. The main objectives are: (a) to create a framework for obtaining disaggregated, appliance-specific feedback about electricity consumption in a building by extracting high-value information from low-cost data sources; and (b) to investigate and develop data mining and machine learning algorithms for making use of appliance-specific electricity data, in order to provide users with recommendations on how to optimize their energy consumption and understand the effects of their energy-related decisions. A series of residential buildings in Pittsburgh, PA will serve as a test-bed for evaluating and validating our proposed approach. Blueroof Technologies, a non-profit corporation located in McKeesport, PA that researches, develops and provides affordable senior-citizen housing with integrated sensor networks and building automation systems, will provide access to their Research Cottages for this project. Similarly, Robert Bosch LLC, a leading global provider of consumer goods and building technology, will provide additional technical research assistance and expertise.The main scientific merit of the project is the development of a framework for evaluating energy-use-disaggregation methods according to their value for promoting energy conservation. The resulting data sets will be large enough to produce significant conclusions about the feasibility and effectiveness of the technology, and allow for the development of new models about the trends and patterns of appliance usage in buildings. Broader impacts of this research include providing a foundation for future cyber-physical systems by inexpensively obtaining real-time appliance-level data. Such data can be used to help reduce the energy consumption of buildings by revealing the relationship between users' behavior and electricity consumption in buildings. The proposed industry-university collaborative research effort with Bosch will ensure that the technology and scientific contributions are steered toward innovative solutions that are practical for adoption in the market. Furthermore, the project will have significant diversity contributions by attracting minority students through collaboration with the University of Maryland Eastern Shore, a land-grant, historically black college with a diverse student body. Finally, a series of planned industry seminars, workshops and the publication of journal articles will allow further dissemination of the work.